Frontal Crash Simulation Research Articles

Efficient injury risk predictions for a diverse population using parametric human modeling and inducing points in Gaussian processes

Objective The objective of this study is to use parametric human modeling and machine learning methods to identify representative occupants that can account for injury variations among a more diverse population with a limited simulation budget. Method A maximal projection method was used to sample 100 occupants, considering the variations in stature, weight, and sitting height. An automated mesh morphing method was used to morph the THUMS v4.1 midsize male model into the target geometries. US-NCAP frontal crash simulations were conducted with morphed human models and validated vehicle/restraint models. Surrogate models based on the Gaussian Process (GP) method were trained to find inducing points (IP), here defined as a small number of representative occupants whose outcomes could be used to accurately estimate the variations in the injury risks and patterns throughout the population. Statistical analysis was conducted to validate the IPs’ coverage of total variation by illustrating the IP distribution. Restraint optimization was performed at IPs to yield an enhanced restraint system. The method was validated through comparisons among the predicted injury risks under the optimal and baseline designs. Results Only 20 IPs were needed to sufficient to properly represent the variations in the injury risks and patterns in the whole population with acceptable accuracy. Compared to the surrogate model built from 100 crash simulations, the IP-based surrogate models incurred only 0.4% and 1.8% errors in head injury risks for males and females, respectively. Regarding the injury risks on the chest and lower extremities, the IP-based surrogate models resulted in less than 0.1% and 0.5% errors for males and females, respectively. The FE simulations indicated that the optimal restraint system design reduced the injury risk by relatively 16% and 13% for male and female respectively when delta-V = 25 (mph), and 47% and 27% for male and female when delta-V = 35 (mph). Significance of results The study proposed a method to generate more accurate injury risk predictions for a more diverse population under a limited simulation budget. Simulations using IPs may enable restraint system optimization to be conducted more efficiently while reducing injury risks across a more diverse population.

The effectiveness of Q6 and PIPER 6-year-old models on quantification of the change of child sitting posture with AEB and its impact on child’s injures in frontal crash

Objective Automatic Emergency Braking (AEB) has a direct impact on the effectiveness of the restraint systems in providing protection toward child occupants. The objective is to evaluate the effectiveness of Q6 and PIPER 6-year-old models in predicting the kinematic responses of child models, and further to quantify and analyze the child injuries during a frontal crash with and without AEB. Methods The finite element model of a booster seat has been validated through a full vehicle test. Based on the validated finite element model, two sled test finite element models for the rear seat booster seat with Q6 and PIPER 6-year-old models were constructed. AEB condition was imposed on above the two models and the kinematic responses of sitting posture including head, neck and chest have been compared in detail. The peak head displacement and neck curvature of Q6 dummy and PIPER 6-year-old models have been compared with the test data from child volunteers. Based on the child model with better predictive capability for kinematic response under AEB, child injuries were evaluated and analyzed for the 50 km/h frontal crash test with and without AEB. Last, this study discussed the effects of internal neck and chest structure difference between Q6 and PIPER 6-year-old models on child kinematic response and the injury risks. Results Under AEB condition, PIPER 6-year-old model has higher head displacement and lower trunk displacement than Q6 dummy model, and the peak head displacement and neck curvature of PIPER 6-year-old model are similar to the test data of child volunteers. During the 50 km/h frontal crash simulation with pre-crash AEB, the HIC15, Head acceleration 3 ms, Nij decrease 43.7%, 19.6% and 28.8%, respectively and the chest deflection increases 15.5% compared to the simulation without AEB. Conclusions This study shows that PIPER 6-year-old model is more suitable for the quantification of sitting posture change under AEB due to its higher biofidelity. The pre-crash AEB can substantially reduce the head, neck injuries. But it also increases the chest injury due to the chest pre-compression. Future efforts are recommended to lower the child chest injury by integrating AEB with active pre-tensioning seatbelts.

Restraint System Optimizations Using Diverse Human Body Models in Frontal Crashes

<div><b>Objective:</b> This study aimed to optimize restraint systems and improve safety equity by using parametric human body models (HBMs) and vehicle models accounting for variations in occupant size and shape as well as vehicle type.</div> <div><b>Methodology:</b> A diverse set of finite element (FE) HBMs were developed by morphing the GHBMC midsize male simplified model into statistically predicted skeleton and body shape geometries with varied age, stature, and body mass index (BMI). A parametric vehicle model was equipped with driver, front passenger, knee, and curtain airbags along with seat belts with pretensioner(s) and load limiter and has been validated against US-NCAP results from four vehicles (Corolla, Accord, RAV4, F150). Ten student groups were formed for this study, and each group picked a vehicle model, occupant side (driver vs. passenger), and an occupant model among the 60 HBMs. About 200 frontal crash simulations were performed with 10 combinations of vehicles (n = 4) and occupants (m = 8). The airbag inflation, airbag vent size, seatbelt load limiter, and steering column collapse force were varied to reach better occupant protection. The joint injury probability (Pjoint) combining head, neck, chest, and lower extremity injury risks was used for the design optimization. Injury risk curves were scaled based on the skeleton size and shape of each HBM.</div> <div><b>Results and Conclusions:</b> We observed that tall and heavier male occupants tend to strike through the airbag leading to higher head injury risk; older and female occupants tend to sustain higher chest injury risk, while obese occupants tend to have higher lower extremity injury risk. After design optimizations, the average <i>P</i>joint was reduced from 0.576 ± 0.218 to 0.343 ± 0.044. The airbag inflation and venting were found to be highly effective in head protection, while the belt load limit and steering column force were sensitive to chest injury risks. Conflicting parameter effects were found between head and chest injuries and among different occupants, highlighting the complexity of achieving safety equity across a diverse population. This study demonstrated the benefit of adaptive restraint systems for a diverse population.</div>

Adaptive restraint design for a diverse population through machine learning.

Using population-based simulations and machine-learning algorithms to develop an adaptive restraint system that accounts for occupant anthropometry variations to further enhance safety balance throughout the whole population. Two thousand MADYMO full frontal impact crash simulations at 35 mph using two validated vehicle/restraint models representing a sedan and an SUV along with a parametric occupant model were conducted based on the maximal projection design of experiments, which considers varying occupant covariates (sex, stature, and body mass index) and vehicle restraint design variables (three for airbag, three for safety belt, and one for knee bolster). A Gaussian-process-based surrogate model was trained to rapidly predict occupant injury risks and the associated uncertainties. An optimization framework was formulated to seek the optimal adaptive restraint design policy that minimizes the population injury risk across a wide range of occupant sizes and shapes while maintaining a low difference in injury risks among different occupant subgroups. The effectiveness of the proposed method was tested by comparing the population-wise injury risks under the adaptive design policy and the traditional state-of-the-art design. Compared to the traditional state-of-the-art design for midsize males, the optimal design policy shows the potential to further reduce the joint injury risk (combining head, chest, and lower extremity injury risks) among the whole population in the sedan and SUV models. Specifically, the two subgroups of vulnerable occupants including tall obese males and short obese females had higher reductions in injury risks. This study lays out a method to adaptively adjust vehicle restraint systems to improve safety balance. This is the first study where population-based crash simulations and machine-learning methods are used to optimize adaptive restraint designs for a diverse population. Nevertheless, this study shows the high injury risks associated with obese and female occupants, which can be mitigated via restraint adaptability.

Coach crashworthiness and failure analysis during a frontal impact

Accidents involving coaches may endanger the physical integrity of their occupants, since the driver stands very close to the collision region. In the event of a frontal impact, there is a violation of the driver's residual operational space, which depends on the energy of the crash, and this may jeopardize the driver's safety. The most decisive factors in achieving a successful design of structural vehicles is to design innovative solutions that safely control the high energy released as a consequence of the high accelerations involved during impacts. Long-course coaches currently lack design techniques and technologies to absorb in a controlled way the kinetic energy released in the collision. Thus, to fulfill this gap in the passive safety of these vehicles, it is necessary to conduct structural optimization research, to improve the passive safety in the eventual event of a frontal collision. The main goal of this research is to develop new solutions for passive safety used in coaches. To this end, a feasibility study involving experimental and numerical techniques was conducted to assess the improvement of driver safety in case of a frontal impact. This study addresses the need for improved experimental validation and fills a literature gap by developing a realistic testing system and incorporating advanced monitoring techniques for evaluating frontal collisions in vehicles, so a M3 Class III coach was used to conduct this study. Experimentally, the vehicle was subjected to a frontal crash test, whereby the ECE Regulation R29 was considered as the baseline, despite focusing on the certification of heavy vehicles with separate driver's cab. Since no standards are available focusing on coaches, the ECE R29 was used and adapted to the studied model. The experimental testing setup comprises a 2500kg pendulum supported by two steel bars was used. When released it collides with the structure, anchored to the ground, with an energy of 55kJ. Monitoring techniques were employed to track the structure, namely Digital Image Correlation (DIC), strain gauges, and accelerometers. These were placed at specific points to accurately assess the damage evolution of the structure. The experimental results were used to validate the numerical results, obtained using VPS/PamCrash® by FEM techniques. The frontal crash simulation was performed using the Finite Element Method, with an explicit dynamic analysis. Strain evolution, accelerations, and displacements were obtained and compared with the experimental results. Furthermore, the evolution of the kinetic energy is plotted and compared with the reference value of the standard. Through the different obtained outcomes, a determination could be made whether the current models meet the safety criteria or whether a proposed solution is required to enhance its performance. According to the standard guidelines, the present structure has no potential to meet the essential safety requirements. In the future, new alternatives should be explored, leading to a structure that can efficiently absorb all the energy released in the experiment under controlled conditions.

Crash topology optimization for front-end safety parts of battery electric vehicle using an improved equivalent static loads method

Crash topology optimization is a typical nonlinear dynamic response structural topology optimization problem, which is one of the most difficult problem in the structural design field. The equivalent static load method (ESLM) provides a well-defined pattern to solve such difficult problems, which can convert a nonlinear dynamic response optimization into multi-load steps optimization problem with the equivalent static loads (ESLs). However, due to the large deformation in the crash condition and nodal characteristics of the ESLs, it is hard to solve the crash topology optimization directly using the standard ESLM. To expand the application scope of the ESLM, an improved ESLs calculation method is proposed by using the model order reduction method and energy principle, which only acting on some nodes and can be scaled adaptively. Correspondingly, to enrich the connotation of topology optimization, a crash topology optimization method is proposed by using the improved ESLs, which can solve the numerical problems in the design domain by guaranteeing the topology optimization with the improved ESLs perform in the linear rang. First, the principle of the standard ESLM is introduced, and corresponding problems and deficiencies in solving the crash topology optimization are summarized. Then, to solve the above problems, the improved ESLs calculation method is proposed. Meanwhile, the corresponding crash topology strategy is proposed based on the improved ESLs. Finally, to verify the effectiveness and engineering application value of the proposed crash topology optimization method, a test-verified frontal crash simulation model of the BEV front-end is established, and their safety parts are redesigned by using the proposed method. The results show that, the proposed method can effectively solve the crash topology optimization of thin-walled structures under large deformation crash condition. This method also provides a new idea and practical method for the crashworthiness and lightweight design of automobile structures.

Frontal crashworthiness optimization for a light-duty vehicle based on a multi-objective reliability method

In the current research, the main method to improve passenger safety in collision accidents and achieve lightweight of body-in-white (BIW) is deterministic optimization. Due to the perturbations of the design variables, the deterministic optimization results will be invalid. To solve this problem, a multi-objective reliability method based on integrating surrogate model and Six-Sigma criteria is proposed. As an example, a finite element model of a light-duty vehicle has been developed and validated by full-scale crash test. Through analyzing the overall energy absorption performance during frontal crash simulation, six main parts have screened, and their thickness values have been selected as design variables. Increasing energy absorption and reducing the weight of the structure were selected as design objectives. The front wall invasion ( D ), the peak acceleration ( A ) and the energy difference ΙΔEΙ absorbed by the left and right side stringer are as constrains. Take the design variables obey normal distribution, and use a genetic algorithm method to generate Pareto solutions. The Pareto solutions of different iteration numbers with a sigma level of 4.5 are analyzed, and the results show that both deterministic optimization and reliability optimization can increase energy absorption. While deterministic optimization increases total energy absorption by 7.6%, but the total weight is increased by 6.9%. And the reliability of the two constraint functions front wall invasion and peak acceleration are lower than 60%. The reliability optimization decreases the weight by 5.3% and increases the energy absorption by 11.7%. Meanwhile, the value of constraint functions are lower, which is beneficial to the crashworthiness of the vehicle, and the reliability of them reaches more than 99%.

Is optimized restraint system for an occupant with obesity different than that for a normal BMI occupant?

Objective To optimize the components of restraint systems for protecting obese (BMI = 35 kg/m2) and normal BMI (BMI = 25) human body models (HBMs) in frontal crash simulations, and to compare the two optimized designs. Methods The Life Years Lost metric, which incorporates the risk of injury and long-term disability to different body regions, was used as the optimization objective function. Parametric simulations, sampled from a 15-parameter design space using the Latin Hypercube technique, were performed and metamodels of the HBM responses were developed. A genetic algorithm was applied to the metamodels to identify the optimized designs. Results While most of the restraint parameters between the optimized design for obese and normal BMI HBMs were similar, the main difference was that the restraint for the obese HBM included an under-the-seat airbag, which mitigated its lower extremity excursion, improved its torso kinematics, and decreased its lower extremity and lumbar spine injury risks. The optimized designs for both HBMs included an inflatable seat belt, which reduced the risk of thoracic injury. Conclusions The design recommendations from this study should be considered to improve safety of occupants with obesity.

Dynamic frontal crash performance of old and used child restraint systems

Objective To examine the effect of age on the dynamic performance of child restraint systems in frontal crashes. Methods A sample of used (3-269 months from manufacture) and newly purchased child restraints were subjected to frontal crash simulations of more than 56 km/h and peak deceleration approximately 33 g on a deceleration sled. Restraints were monitored for evidence of damage before and after each impact. Anthropometric test device (ATD) head and chest responses and peak head excursions were recorded for rearward facing restraints using the Q1 ATD and for forward facing restraints and booster seats using the Q6 ATD. The influence of restraint age on peak 3 ms head acceleration, HIC15, head excursion, peak 3 ms chest acceleration and restraint damage were analyzed. Results In all impacts, the ATD remained within the restraint and secured to the test bench demonstrating the crash protection offered by the old and used restraints. There was no apparent relationship between ATD responses and restraint age for any restraint type. Older forward facing restraint systems had a very modest increase in forward head excursion (R2 = 0.59, p = 0.001) of 0.27 mm for each month of age (95% CI, 0.13 mm − 0.42 mm). This equates to a 0.7% increase in the minimum measured excursion per year of restraint age. There was also a small increased likelihood of critical damage to the restraints in the simulated crashes per month of restraint age (OR 1.031, 95% CI 1.010-1.069). Conclusions Overall, degradation in restraint dynamic performance in older restraints, including some that are much older than the currently recommended 10-year lifetime, is minimal. However newer restraints may provide better protection due to marginal improvements in restraint design over time. Furthermore, the results of this study confirm previous recommendations that restraints should not be re-used after crash involvement.

Analysis of Front Impact Performance of Hybrid Electric Bus Body

In this paper, based on the finite element software Hyperworks and ls-dyna, with the vehicle frontal impact occupant protection (GB11551-2014) as a reference standard, the frontal crash simulation analysis was carried out on the EQ6110HEV6 hybrid electric bus, comprehensive analysis of the body deformation, pilot living space, the door deformation, center of mass acceleration and driver seat center floor acceleration, on the vehicle collision safety is evaluated. Based on the analysis results, the front frame, bottom frame and door parts of the bus are improved, and the collision simulation of the improved bus is carried out. Through the comparison and analysis of the results before and after the improvement, the collision performance of the hybrid bus is significantly improved, which verifies the effectiveness of the improvement scheme.

Engineering Design Optimization by Dynamic Cluster based Framework using Mixture Surrogates

The real-world engineering optimization problems utilize complex computational methods like finite element frameworks. These approaches are computationally costly and need high solution time. The work pays attention on finding the optimal solution to these complex engineering problems by using Surrogate Models (SM). SMs are mathematical models, which are utilized to minimize the required number of such costly function evaluations at the time of the optimization cycles. Instead of optimizing the Design Space (DS) as a whole, subregion based strategies are found to be effectual, especially in the cases where prior knowledge of optimal solution is unavailable. In the present work, a surrogate centered optimization scheme is presented for local search, which dynamically sub-divides the DS into an optimum number of sub-regions by choosing the best cluster evaluation techniques as followed by the selection of best mixture SMs for each optimization cycle. For all objective functions and constraint functions in every sub-region, the mixture SMs are created by a combination of two or more single SMs. The MATSuMoTo, the Matlab based SM Toolbox by Juliane Muller and Robert Piché has been adapted for the creation and selection of best mixture SM. In this method, an individual surrogate is combined by utilizing the DempsterShafer theory (DST). Besides the above local search, a global search module is also introduced for ensuring faster convergence. This approach is tested on a constrained optimization benchmark test problem with smaller, disconnected feasible regions. It is perceived that the proposed algorithm accurately located all the local and global optima points with minimum function evaluations. The approach is applied to engineering problems like optimization of Machine Tool Spindle (MTS) design and frontal crash simulation on a full car body. For these engineering application problems also, mixture SMbased sub-region based search strategy is utilized to attain most accurate global optimum solution with a minimal number of costly function evaluations.

Frontal crash simulations using parametric human models representing a diverse population

Objective: Analyses of crash data have shown that older, obese, and/or female occupants have a higher risk of injury in frontal crashes compared to the rest of the population. The objective of this study was to use parametric finite element (FE) human models to assess the increased injury risks and identify safety concerns for these vulnerable populations.Methods: We sampled 100 occupants based on age, sex, stature, and body mass index (BMI) to span a wide range of the U.S. adult population. The target anatomical geometry for each of the 100 models was predicted by the statistical geometry models for the rib cage, pelvis, femur, tibia, and external body surface developed previously. A regional landmark-based mesh morphing method was used to morph the Global Human Body Models Consortium (GHBMC) M50-OS model into the target geometries. The morphed human models were then positioned in a validated generic vehicle driver compartment model using a statistical driving posture model. Frontal crash simulations based on U.S. New Car Assessment Program (U.S. NCAP) were conducted. Body region injury risks were calculated based on the risk curves used in the US NCAP, except that scaling was used for the neck, chest, and knee–thigh–hip injury risk curves based on the sizes of the bony structures in the corresponding body regions. Age effects were also considered for predicting chest injury risk.Results: The simulations demonstrated that driver stature and body shape affect occupant interactions with the restraints and consequently affect occupant kinematics and injury risks in severe frontal crashes. U-shaped relations between occupant stature/weight and head injury risk were observed. Chest injury risk was strongly affected by age and sex, with older female occupants having the highest risk. A strong correlation was also observed between BMI and knee–thigh–hip injury risk, whereas none of the occupant parameters meaningfully affected neck injury risks.Conclusions: This study is the first to use a large set of diverse FE human models to investigate the combined effects of age, sex, stature, and BMI on injury risks in frontal crashes. The study demonstrated that parametric human models can effectively predict the injury trends for the population and may now be used to optimize restraint systems for people who are not similar in size and shape to the available anthropomorphic test devices (ATDs). New restraints that adapt to occupant age, sex, stature, and body shape may improve crash safety for all occupants.

Head Injury Analysis of Vehicle Occupant in Frontal Crash Simulation: Case Study of ITB’s Formula SAE Race Car

In the present study, frontal crash simulations were conducted to determine the effect of various car speeds against the Head Injury Criterion (HIC), a measure of the likelihood of head injury arising from impact. The frontal impact safety of ITB's formula SAE race car designed by students was evaluated as a case study. LS-DYNA®, an explicit finite element code for non-linear dynamic analysis was utilized in the analysis. To analyze head injury, a two-step simulation was conducted. In the first step, a full-frontal barrier test was simulated without incorporating a dummy inside the car. The output was the deceleration data of the car, which was used as input in the second step, a sled test simulation. In the sled test, only the cockpit and dummy were modeled. The effect of deceleration to the head of the dummy was then evaluated. The results show that HIC values at an impact speed of 7 m/s (25 km/h) to 11 m/s (40 km/h) were below the safe limit and still in the safe zone. However, the HIC values will exceed the safe limit when the speed of impact is the same as or greater than 12 m/s (43 km/h).

Crashworthiness Analysis of Electric Vehicle With Energy-Absorbing Battery Modules

As a clean energy technology, the development of electric vehicles (EVs) is challenged by lightweight design, battery safety, and range. In this study, our simulations indicate that using a flexible structure of battery module has the potential to overcome the limitations in battery-powered EVs, contributing to a new design. Specifically, we focus on optimizing the structure of vehicle battery packs, aiming to improve the crashworthiness of EVs through frontal crash simulations. In addition, by considering battery packs as energy-absorption components, it is found that occupant compartment acceleration (OCA) is greatly reduced at an optimal working pressure of 4 MPa for battery module.

The effect of including a fetus in the uterus model on the risk of fetus mortality through drop test and frontal crash simulations

ABSTRACTComputational modelling is an effective way of estimating the risk of injuries and fatalities in road traffic accidents. Computational pregnant occupant modelling has an additional important role in the investigation of the risk of fetus mortality in crash test simulations. In this paper, the effect of including the fetus in the uterus of the pregnant occupant model is investigated. First, isolated drop test simulations with the uterus of the computational pregnant occupant model, ‘Expecting’, with and without a fetus are used to show the effect of the presence of fetus in the uterus model. Then ‘Expecting’ with and without the fetus is used with varying levels of restraint system use, such as fully restrained, ‘seatbelt only’, ‘airbag only’ and ‘no restraint’, in frontal crash simulations, representing five levels of impacts. Maximum strains developed in the uteroplacental interface with and without a fetus are compared in every case. Both simulations predict higher risks of placental abruption when the fetus is included in the model. Simulations with and without a fetus model show that inclusion of a 38-week fetus model causes higher strains in the placental region of uterus.

A Simulation Study on the Efficacy of Advanced Belt Restraints to Mitigate the Effects of Obesity for Rear-Seat Occupant Protection in Frontal Crashes

Objective: Recent field data analyses have shown that the safety advantages of rear seats relative to the front seats have decreased in newer vehicles. Separately, the risks of certain injuries have been found to be higher for obese occupants. The objective of this study is to investigate the effects of advanced belt features on the protection of rear-seat occupants with a range of body mass index (BMI) in frontal crashes.Methods: Whole-body finite element human models with 4 BMI levels (25, 30, 35, and 40 kg/m2) developed previously were used in this study. A total of 52 frontal crash simulations were conducted, including 4 simulations with a standard rear-seat, 3-point belt and 48 simulations with advanced belt features. The parameters varied in the simulations included BMI, load limit, anchor pretensioner, and lap belt routing relative to the pelvis. The injury measurements analyzed in this study included head and hip excursions, normalized chest deflection, and torso angle (defined as the angle between the hip–shoulder line and the vertical direction). Analyses of covariance were used to test the significance (P <.05) of the results.Results: Higher BMI was associated with greater head and hip excursions and larger normalized chest deflection. Higher belt routing increased the hip excursion and torso angle, which indicates a higher submarining risk, whereas the anchor pretensioner reduced hip excursion and torso angle. Lower load limits decreased the normalized chest deflection but increased the head excursion. Normalized chest deflection had a positive correlation with maximum torso angle. Occupants with higher BMI have to use higher load limits to reach head excursions similar to those in lower BMI occupants.Discussion and Conclusion: The simulation results suggest that optimizing load limiter and adding pretensioner(s) can reduce injury risks associated with obesity, but conflicting effects on head and chest injuries were observed. This study demonstrated the feasibility and importance of using human models to investigate protection for occupants with various BMI levels. A seat belt system capable of adapting to occupant size and body shape will improve protection for obese occupants in rear seats.

Injury risk prediction using elderly digital human body model

Frontal crash sled simulation is performed with Hybrid III dummy and elderly human body model to assess the relative high injury risk of older population. The sled model representing a typical driver side seat with a restraint system is validated against the test result. The current restraint design is tailored to the younger generation and found to be less effective for the older driver. The 48kph frontal crash simulation predicted AIS 4 level chest injury (7 rib fractures) of the elderly driver while 10 % risk of rib fracture was found with the Hybrid III dummy.

Light weight replacement and the optimization design of bumper beam based on crash safety

Bumper beam is one of the key structural parts,which plays an important role in the frontal crashes of automobile.With the global trend of light-weighted automotive parts,the light weight of bumper beam attracts extensive attention of automobile manufacturers,and hot stamping technology with significant weight advantage has become one of the main light weight measures for bumper beam.The quasi-static press,low speed crash and frontal crash simulation models of bumper beam were established according to its actual working conditions in the automobile crashes.The feasibility of replacing normal steel bumper beam with hot stamping bumper beam was analyzed.Meanwhile,the stiffeners in the front face of hot stamping bumper beam were optimized with topography optimization in order to further improve its performances.

A computational study of injury severity and pattern sustained by overweight drivers in frontal motor vehicle crashes

The objective of this study was to examine the role of body mass and subcutaneous fat in injury severity and pattern sustained by overweight drivers. Finite element models were created to represent the geometry and properties of subcutaneous adipose tissue in the torso with data obtained from reconstructed magnetic resonance imaging data-sets. The torso adipose tissue models were then integrated into the standard multibody dummy models together with increased inertial parameters and sizes of the limbs to represent overweight occupants. Frontal crash simulations were carried out considering a variety of occupant restraint systems and regional body injuries were measured. The results revealed that differences in body mass and fat distribution have an impact on injury severity and pattern. Even though the torso adipose tissue of overweight subjects contributed to reduce abdominal injury, the momentum effect of a greater body mass of overweight subjects was more dominant over the cushion effect of the adipose tissue, increasing risk of other regional body injuries except abdomen. Through statistical analysis of the results, strong correlations (p < 0.01) were found between body mass index and regional body injuries except neck injury. The analysis also revealed that a greater momentum of overweight males leads to greater forward torso and pelvic excursions that account for higher risks (p < 0.001) of head, thorax and lower extremity injury than observed in non-overweight males. The findings have important implications for improving the vehicle and occupant safety systems designed for the increasing global obese population.

Crashworthiness optimisation of vehicle structures with magnesium alloy parts

This paper explores the effects of replacing the baseline steel with lightweight magnesium alloy parts on crashworthiness characteristics and optimum design of a full-vehicle model. Full frontal, offset frontal and side crash simulations are performed on a validated 1996 Dodge Neon model using explicit nonlinear transient dynamic finite element analyses in LS-DYNA to obtain vehicle responses such as crash pulse, intrusion distance, peak acceleration and internal energy. Twenty-two parts of the vehicle body structure are converted into AZ31 magnesium alloy with adjustable wall thickness while the remaining parts are kept intact. The magnesium alloy material model follows a piecewise linear plasticity law considering separate tension and compression properties and maximum plastic strain failure criterion. Six different metamodelling techniques including optimised ensemble are developed and tuned for predictions of crash-induced responses within the design optimisation process. The crashworthiness optimisation problem is solved using the sequential quadratic programming method with most accurate surrogate models of structural responses considering both constrained single- and multi-objective formulations. The results show that under the combined crash scenarios with the selected material models and design constraints, the vehicle model with magnesium alloy parts can be optimised to maintain or improve its crashworthiness characteristics with up to 50% weight savings in the redesigned parts.